I. Field of the Invention
The present invention relates to image processing. More specifically, the present invention relates to a quality based compression scheme for image signals utilizing adaptively sized blocks and sub-blocks of encoded discrete cosine transform coefficient data.
II. Description of the Related Art
In the field of transmission and reception of video signals such as are used for projecting xe2x80x9cfilmsxe2x80x9d or xe2x80x9cmoviesxe2x80x9d, various improvements are being made to image compression techniques. Many of the current and proposed video systems make use of digital encoding techniques. Digital encoding provides a robustness for the communications link which resists impairments such as multipath fading and jamming or signal interference, each of which could otherwise seriously degrade image quality. Furthermore, digital techniques facilitate the use signal encryption techniques, which are found useful or even necessary for governmental and many newly developing commercial broadcast applications.
High definition video is an area which benefits from improved image compression techniques. When first proposed, over-the-air transmission of high definition video (or even over-wire or fiber-optical transmission) seemed impractical due to excessive bandwidth requirements. Typical wireless, or other, transmission systems being designed did not readily accommodate enough bandwidth. However, it has been realized that compression of digital video signals may be achieved to a level that enables transmission using reasonable bandwidths. Such levels of signal compression, coupled with digital transmission of the signal, may enable a video system to transmit with less power and with greater immunity to channel impairments while occupying a more desirable and useful bandwidth.
Many compression techniques available offer significant levels of compression, but result in a degradation of the quality of the video signal. Typically, techniques for transferring compressed information require the compressed information to be transferred at a constant bit rate.
One compression technique capable of offering significant levels of compression while preserving the desired level of quality for video signals utilizes adaptively sized blocks and sub-blocks of encoded Discrete Cosine Transform (DCT) coefficient data. This technique will hereinafter be referred to as the Adaptive Block Size Discrete Cosine Transform (ABSDCT) method. This technique is disclosed in U.S. Pat. No. 5,021,891, entitled xe2x80x9cAdaptive Block Size Image Compression Method And System,xe2x80x9d assigned to the assignee of the present invention and incorporated herein by reference. DCT techniques are also disclosed in U.S. Pat. No. 5,107,345, entitled xe2x80x9cAdaptive Block Size Image Compression Method And System,xe2x80x9d assigned to the assignee of the present invention and incorporated herein by reference. Further, the use of the ABSDCT technique in combination with a Differential Quadtree Transform technique is discussed in U.S. Pat. No. 5,452,104, entitled xe2x80x9cAdaptive Block Size Image Compression Method And System,xe2x80x9d also assigned to the assignee of the present invention and incorporated herein by reference. The systems disclosed in these patents utilize what is referred to as xe2x80x9cintra-framexe2x80x9d encoding, where each frame of image data is encoded without regard to the content of any other frame. Using the ABSDCT technique, the achievable data rate may be reduced from around 1.5 billion bits per second to approximately 50 million bits per second without discernible degradation of the image quality.
The ABSDCT technique may be used to compress either a black and white or a color image or signal representing the image. The color input signal may be in a YIQ format, with Y being the luminance, or brightness, sample, and I and Q being the chrominance, or color, samples for each 4xc3x974 block of pixels. Other known formats such as the YUV, YCbCy or RGB formats may also be used. Because of the low spatial sensitivity of the eye to color, most research has shown that a sub-sample of the color components by a factor of four in the horizontal and vertical directions is reasonable. Accordingly, a video signal may be represented by four luminance components and two chrominance components.
Using ABSDCT, a video signal will generally be segmented into blocks of pixels for processing. For each block, the luminance and chrominance components are passed to a block interleaver. For example, a 16xc3x9716 (pixel) block may be presented to the block interleaver, which orders or organizes the image samples within each 16xc3x9716 block to produce blocks and composite sub-blocks of data for discrete cosine transform (DCT) analysis. The DCT operator is one method of converting a time and spatial sampled signal to a frequency representation of the same signal. By converting to a frequency representation, the DCT techniques have been shown to allow for very high levels of compression, as quantizers can be designed to take advantage of the frequency distribution characteristics of an image. In a preferred embodiment, one 16xc3x9716 DCT is applied to a first ordering, four 8xc3x978 DCTs are applied to a second ordering, 16 4xc3x974 DCTs are applied to a third ordering, and 64 2xc3x972 DCTs are applied to a fourth ordering.
The DCT operation reduces the spatial redundancy inherent in the video source. After the DCT is performed, most of the video signal energy tends to be concentrated in a few DCT coefficients. An additional transform, the Differential Quad-Tree Transform (DQT), may be used to reduce the redundancy among the DCT coefficients.
For the 16xc3x9716 block and each sub-block, the DCT coefficient values and the DQT value (if the DQT is used) are analyzed to determine the number of bits required to encode the block or sub-block. Then, the block or the combination of sub-blocks that requires the least number of bits to encode is chosen to represent the image segment. For example, two 8xc3x978 sub-blocks, six 4xc3x974 sub-blocks, and eight 2xc3x972 sub-blocks may be chosen to represent the image segment.
The chosen block or combination of sub-blocks is then properly arranged in order into a 16xc3x9716 block. The DCT/DQT coefficient values may then undergo frequency weighting, quantization, and coding (such as variable length coding) in preparation for transmission. Although the ABSDCT technique described above performs remarkably well, it is computationally intensive. Thus, compact hardware implementation of the technique may be difficult.
Alternative techniques that make hardware implementation more efficient offer certain advantages. Some systems utilize adaptively sized blocks and sub-blocks of Discrete Cosine Transform (DCT) coefficient data. Although portions of DCT based systems utilize quality as a compression parameter, other portions of the data are based on the encoding rate, as opposed to using a quality-based metric. An example of such a coding rate based paramter is the quantization step selection of the contrast based adaptive block size image compression algorithm.
The present invention is a quality based system and method of image compression that utilizes adaptively sized blocks and sub-blocks of Discrete Cosine Transform coefficient data and a quality based quantization scale factor. A block of pixel data is input to an encoder. The encoder comprises a block size assignment (BSA) element, which segments the input block of pixels for processing. The block size assignment is based on the variances of the input block and further subdivided blocks. In general, areas with larger variances are subdivided into smaller blocks, and areas with smaller variances are not be subdivided, provided the block and sub-block mean values fall into different predetermined ranges. Thus, first the variance threshold of a block is modified from its nominal value depending on its mean value, and then the variance of the block is compared with a threshold, and if the variance is greater than the threshold, then the block is subdivided.
The block size assignment is provided to a transform element, which transforms the pixel data into frequency domain data. The transform is performed only on the block and sub-blocks selected through block size assignment. The transform data then undergoes scaling through quantization and serialization. Quantization of the transform data is quantized based on an image quality metric, such as a scale factor that adjusts with respect to contrast, coefficient count, rate distortion, density of the block size assignments, and/or past scale factors. Zigzag scanning may also be utilized to serialize the data to produce a stream of data. The stream of data may be coded by a variable length coder in preparation of transmission. The encoded data is sent through a transmission channel to a decoder, where the pixel data is reconstructed in preparation for display.
It is a feature and advantage of the invention to provide a quality based image compression system.
It is another feature and advantage of the invention to allow flexible image quality control through management of the bit rate on a frame by frame basis.
It is another feature and advantage of the invention to allow flexible image quality control through management of the bit rate on a block by block basis.
It is another feature and advantage of the invention to maintain quality image compression and bit rate control of data accompanying activities such as bursts of motion.
It is another feature and advantage of the invention to use signal to noise ratio parameters to quantify image quality.
It is another feature and advantage of the invention to utilize a quantization scale factor that adjusts with respect to the contrast of the image.
It is another feature and advantage of the invention to utilize a quantization scale factor that adjusts with respect to the AC coefficient count of the DCT blocks that comprise an image.
It is another feature and advantage of the invention to utilize a quantization scale factor that adjusts with respect to the distortion and bit rate between frames.
It is another feature and advantage of the invention to utilize a quantization scale factor that adjusts with respect to past quantization scale factors.